Bias removal in prbs based channel estimation

ABSTRACT

A system includes a pseudorandom binary sequence (PRBS) generator configured to generate a first PRBS and a second PRBS and an exclusive-OR logic configured to exclusive-OR the first PRBS and the second PRBS to compute a third PRBS. The system also includes an adder, a correlator and a corrector. The adder adds the third PRBS to input data to compute summed data for transmission of the summed data across the channel. The correlator computes the exclusive-OR of the first PRBS and the second PRBS to reproduce the third PRBS and correlates output data from the channel to the reproduced third PRBS to compute a channel gain error and a channel memory error. The corrector extracts the input data from the output data from the channel using the computed channel gain and memory errors.

BACKGROUND

Many systems involve sending data from a source to a destination througha channel. The channel may introduce gain error and memory error to thedata being transmitted thereby resulting in a degradation of thesignal-to-noise ratio. The accurate recovery of the source input data tothe channel at the output of the channel can be difficult.

SUMMARY

In an embodiment, a system includes a pseudorandom binary sequence(PRBS) generator configured to generate a first PRBS and a second PRBSand an exclusive-OR logic configured to exclusive-OR the first PRBS andthe second PRBS to compute a third PRBS. The system also includes anadder, a correlator and a corrector. The adder adds the third PRBS toinput data to compute summed data for transmission of the summed dataacross the channel. The correlator computes the exclusive-OR of thefirst PRBS and the second PRBS to reproduce the third PRBS andcorrelates output data from the channel to the reproduced third PRBS tocompute a channel gain error and a channel memory error. The correctorextracts the input data from the output data from the channel using thecomputed channel gain and memory errors.

In another embodiment, a system includes a PRBS generator configured togenerate a first PRBS and a second PRBS. The system also includes alogic circuit coupled to the PRBS generator. The logic circuit isconfigured to generate a third PRBS from first PRBS and the second PRBS.The system includes a channel configured to receive input data combinedwith the third PRBS and to output channel output data. A correlator isincluded that is coupled to the PRBS generator and is configured toreceive the first PRBS and the second PRBS, reproduce the third PRBSusing the received first PRBS and the received second PRBS, andcorrelate the output data from the channel to the reproduced third PRBSto compute a channel gain error and a channel memory error. A correctoris coupled to the correlator and is configured to estimate the inputdata from the output data from the channel using the computed channelgain and memory errors.

In yet another embodiment, a method includes generating a first PRBS,generating a second PRBS, and generating a third PRBS using the firstPRBS and the second PRBS. The method further includes injecting thethird PRBS into a channel along with input data, providing the first andsecond PRBS to a correlator, reproducing, by the correlator, the thirdPRBS using the provided first PRBS and the provided second PRBS,correlating the output data from the channel to the reproduced thirdPRBS to compute a channel gain error and a channel memory error, andcorrecting the output data from the channel using the computed channelgain error and memory error to estimate the input data.

BRIEF DESCRIPTION OF THE DRAWINGS

For a detailed description of various examples, reference will now bemade to the accompanying drawings in which:

FIG. 1 shows a system in accordance with various examples; and

FIG. 2 shows a method in accordance with various examples.

DETAILED DESCRIPTION

As noted above, channels can introduce gain and memory error. Sucherrors may cause a degradation to the signal-to-noise ratio (SNR).Various techniques can be employed to estimate the gain error and thememory error of the channel to thereby counteract the SNR degradingeffects. Such techniques involve the use of pseudorandom binarysequences (PRBS). A PRBS may refer to a binary sequence that, whilegenerated with a deterministic algorithm, is difficult to predict andexhibits statistical behavior similar to a truly-random sequence. A PRBSpattern can be added to the input data at the input of the channel, andthe channel's output signal is then correlated with the same PRBSpattern to estimate the channel's gain and memory. Once the channel'sgain and memory errors are estimated, such errors can be removed fromthe output signal of the channel. Unfortunately, in some systems, thePRBS values may couple through unwanted paths into the channel. It canbe very difficult to ensure that PRBS is not added through undesiredpathways into the channel.

The disclosed embodiments address these issues by sending different PRBSinto the channel from what is generated by the PRBS generator and sentto a correlator. First and second PRBS values are generated and thefirst and second PRBS values are uncorrelated to each other. The firstand second uncorrelated PRBS values are then exclusive-OR'd to produce athird PRBS value that is uncorrelated to either of the input PRBSvalues. The resulting third PRBS value is sent into the channel alongwith the input data. The first and second PRBS values are provided tothe correlator which also performs the exclusive-OR operation on thefirst and second PRBS values to produce the third PRBS value. Thecorrelator correlates the output of the channel with the third PRBSvalue and the first and the second PRBS values to correct for theeffects of channel gain, channel memory, and any coupling of PRBS valuesinto the channel through pathways other than the input of the channel atwhich the input data is inserted.

FIG. 1 shows an example of a system 100 (e.g., a communication system)in which input data, x(n), is transmitted across a communication channel110 and corrected based on the principles described herein. The channelmay be implemented as part of any type of electronic system such as ananalog-to-digital converter (ADC). The channel 110 may comprise aplurality of conductors (e.g., wires, traces on a circuit board or die,etc.), drivers, receivers, amplifiers, residue stages, and the like. Thesystem also includes a PRBS generator 102, exclusive-OR logic 104, anadder 106, a correlator 120, and a corrector 130. These components canbe formed from discrete circuit components in some embodiments, orimplemented in a controller executing program instructions such asfirmware.

The PRBS generator 102 generates PRBS values p1(n) and p2(n). The PRBSvalues p1(n) may form a first PRBS, and the PRBS values p2(n) may form asecond PRBS. The PRBS generator 102 may comprise, for example, one ormore linear feedback shift registers (e.g., a Fibonacci linear feedbackshift register, a Galois linear feedback shift register, etc.). A linearfeedback shift register, as used herein, may refer to a shift registerwhose input bit is a linear function of its previous state.

In some embodiments, the PRBS generator 102 generates a sequence ofrandom values and some of the values are selected to be p1(n) and othervalues (e.g., every other value) selected to be p2(n) such that p1(n)and p2(n) are uncorrelated. For example, p1(n) may be a delayed versionof p2(n), or vice versa. A property of a PRBS generator is that the PRBSsequence is uncorrelated to its delayed version so that the correlationbetween p1(n) and p1(n−M) is zero where M is an integer greater than 0.The values of p1(n) and p2(n) are provided to the exclusive-OR logic 104which computes the exclusive-OR operation on the p1(n) and p2(n) valuesthereby generating third PRBS values p3(n). The values of p3(n) areuncorrelated to the p1(n) and p2(n). The p3(n) values are added by adder106 to the input data x(n) and injected into the channel 110 as shown.

As noted above, the channel may have a gain and memory error for theinput data designated as αg and αm, respectively. The p1(n) and p2(n)values may be inserted into the channel at 107 via an undesirablepathway (i.e., a pathway other than through the adder 106 to the inputof the channel. The output of the channel is designated as y(n) and isgiven by:

y(n)=αg[p3(n)+x(n)]+αm[p3(n−1)+x(n−1)]+βg*TF1*[p1(n)+p2(n)]+βm*TF2*[p1(n−1)+p2(n−1)]  (Eq.1)

where p3(n−1), p1(n−1), and p2(n−1) represent the immediately previousvalues of p3, p1, and p2, respectively, and TF1 and TF2 are scalingfactors. The first term in Eq. 1 is αg[p3(n) and x(n)] and representsthe output of the channel from the combination of the current input x(n)and the current PRBS value p3(n). The second term in Eq. 1 is αm[p3(n−1)and x(n−1)] and represents the output of the channel from thecombination of the previous x and p3 values, that is, x(n−1) andp3(n−1). The third term in Eq. 1 is βg*TF1*[p1(n) and p2(n)] andrepresents the output of the channel from the combination of the currentp1 and p2 values through the unintended pathway 107. βg*TF1 is assumedin this equation to be the same for p1(n) as p2(n), but it can bedifferent. If different, p1(n) and p2(n) should be correlated the outputdata to calculate their respective coefficients. This is true as wellfor βm*TF2. The fourth term in Eq. 1 is βm*TF2*[p1(n−1) and p2(n−1)] andrepresents the output of the channel from the combination of theprevious p1 and p2 values through the unintended pathway 107. While Eq.1 only references one previous sample (n−1), the equation is applicablefor other previous samples (n−2), (n−3), etc.

Referring still to FIG. 1, the p1(n) and p2(n) values are provided tothe correlator 120 as well as to the exclusive-OR logic 104. The channeloutput y(n) also is provided to the correlator 120. Collectively thecorrelator 120 and the corrector 130 operate to determine the inputvalues x(n) from the channel output y(n). In Eq. 1 above, y(n) is knownas well as p1(n), p1(n−1), p2(n), and p2(n−1). The values p3(n) andp3(n−1) are computed by the correlator 120 based on p1(n), p1(n−1),p2(n), and p2(n−1), and thus known. P3(n) is the result ofexclusive-OR'ing p1(n) and p2(n), and p3(n−1) is the result ofexclusive-OR'ing p1(n−1) and p2(n−1). Thus, to calculate x(n) from y(n)given Eq. 1, the values of αg, αm, βg*TF1, and βm*TF2 may need to becomputed.

In some embodiments, the correlator 120 correlates y(n) with p3(n) tocompute αg. The value of p3(n) is included in only one term in Eq. (1)(i.e., αg*p3(n)). All other terms in Eq. (1) do not include p3(n) andthus, other than the term αg*p3(n), y(n) is otherwise uncorrelated withp3(n). Thus, correlating y(n) with p3(n) will result in thedetermination of αg. Similarly, the value of p3(n−1) is included in onlyone term in Eq. (1) (i.e., αm*p3(n−1)). All other terms in Eq. (1) donot include p3(n−1) and thus other than the term αm*p3(n−1), y(n) isotherwise uncorrelated with p3(n−1). Thus, correlating y(n) with p3(n−1)will result in the determination of αm. The term βg*TF1 is similarlycalculated by correlating y(n) with p1(n) (or p2(n)) to compute βg*TF1.The term βm*TF2 can be calculated by correlating y(n) with p1(n−1) (orp2(n−1)). In some embodiments, the correlator performs thesecorrelations and computes the values of αg, αm, βg*TF1, and βm*TF2. Thevalues of αg, αm, βg*TF1, and βm*TF2 then may be provided to thecorrector as shown in FIG. 1.

The corrector 130 then corrects the channel output y(n) as:

y′(n)=y(n)−βg*TF1*[p1(n)+p2(n)]−βm*TF2*[p1(n−1)+p2(n−1)]−αg*p3(n)−αm*p3(n−1)  (Eq. 2)

y″(n)=y′(n)/αg=x(n)+(αm/αg)*x(n−1)   (Eq. 3)

y′″(n)=y″(n)−(αm/αg)*y″(n−1)=x(n)+(αm/αg)² *x(n−2)   (Eq. 4)

where y″′(n) is the corrected channel output. The term y′(n) may bereferred to herein as the first intermediate corrected value, and theterm y″(n) may be referred to as the second intermediate correctedvalue. The x(n−2) coefficient may be small enough due to it beingsquared that, in some embodiments, this last term in Eq. (4) can beignored (αm/αg)²*x(n−2). The corrected channel output y″′(n) representsan estimate of the input data x(n). That is, the input data has beenrecalculated by correcting the channel output y(n) for gain and memoryerrors caused by the channel.

FIG. 2 shows a flow chart depicting an example of a method in accordancewith various embodiments. The operations may be performed in the ordershown, or in a different order. Further, the operations may be performedsequentially, or two or more of the operations may be performedconcurrently.

At 200, the method includes generating PRBS data p1(n) and p2(n). Thisoperation may be performed using, for example, a linear feedback shiftregister as explained above. The p1(n) stream is generally uncorrelatedto the p2(n) stream. At 202, the method includes computing theexclusive-OR of p1(n) and p2(n) to generate p3(n). Because p1(n) andp2(n) are uncorrelated, p(3) also is uncorrelated to either p1(n) orp2(n).

At 204, the method includes adding p3(n) to the input data x(n) andinjecting the result into the channel. The initially computed values ofp1(n) and p2(n) are also transmitted to the correlator 120 (operation206). At 208, the correlator exclusive-OR's the received p1(n) with thereceived p2(n) to compute p3(n), which was injected into the channelalong with the input data x(n). The correlator 120 then computes aseries of correlations. At 210, the correlator 120 correlates the outputof the channel, y(n), with p3(n) to compute αg. At 212, the correlator120 correlates y(n) with p3(n−1) to compute αm. At 214, the correlator120 correlates y(n) with p1(n) (or p2(n) to compute βg*TF1. At 216, thecorrelator 120 correlates y(n) with p1(n−1) (or p2(n−1) to computeβm*TF2.

The values of αg, αm, βg*TF1, and βm*TF2 then may be communicated fromthe correlator 120 to the corrector 130 and, at 218, the correctorgenerates the corrected output value y′″(n) asy″(n)−(αm/αg)*y″(n−1)=x(n)+(αm/αg)²*x(n−2) (i.e., Eq. (4) above).Finally, the transmitted data x(n) can then be extracted from thecorrected output y″′(n).

Certain terms are used throughout the following description and claimsto refer to particular system components. As one skilled in the art willappreciate, different companies may refer to a component by differentnames. This document does not intend to distinguish between componentsthat differ in name but not function. In the following discussion and inthe claims, the terms “including” and “comprising” are used in anopen-ended fashion, and thus should be interpreted to mean “including,but not limited to . . . .” Also, the term “couple” or “couples” isintended to mean either an indirect or direct wired or wirelessconnection. Thus, if a first device couples to a second device, thatconnection may be through a direct connection or through an indirectconnection via other devices and connections.

The above discussion is meant to be illustrative of the principles andvarious embodiments of the present invention. Numerous variations andmodifications will become apparent to those skilled in the art once theabove disclosure is fully appreciated. It is intended that the followingclaims be interpreted to embrace all such variations and modifications.

1-14. (canceled)
 15. A system, comprising: a pseudorandom binarysequence (PRBS) generator configured to generate a first PRBS and asecond PRBS; a logic circuit coupled to the PRBS generator andconfigured to generate a third PRBS from first PRBS and the second PRBS;a channel configured to receive input data combined with the third PRBSand to output channel output data; a correlator coupled to the PRBSgenerator and configured to receive the first PRBS and the second PRBS,reproduce the third PRBS using the received first PRBS and the receivedsecond PRBS, and correlate the output data from the channel to thereproduced third PRBS to compute a channel gain error and a channelmemory error; and a corrector coupled to the correlator and configuredto estimate the input data from the output data from the channel usingthe computed channel gain and memory errors.
 16. The system of claim 15,wherein the logic circuit includes an exclusive-OR logic.
 17. (canceled)18. The system of claim 15, further including an adder configured to addthe third PRBS to the input data to compute summed data for transmissionacross the channel. 19-22. (canceled)
 23. The system of claim 15,wherein the PRBS generator includes a linear feedback shift register.24. A method, comprising: generating a first pseudorandom binarysequence (PRBS); generating a second PRBS; generating a third PRBS usingthe first PRBS and the second PRBS; injecting the third PRBS into achannel along with input data; providing the first and second PRBS to acorrelator; reproducing, by the correlator, the third PRBS using theprovided first PRBS and the provided second PRBS; correlating the outputdata from the channel to the reproduced third PRBS to compute a channelgain error and a channel memory error; and correcting the output datafrom the channel using the computed channel gain error and channelmemory error to estimate the input data.
 25. The method of claim 24,wherein generating the third PRBS includes exclusive-OR'ing the firstPRBS and the second PRBS.
 26. (canceled)
 27. The method of claim 24,wherein injecting the third PRBS into the channel along with the inputdata includes adding the third PRBS to the input data to produce asummed data and providing the summed data to the channel. 28-30.(canceled)